Normalization and lossless join decomposition of similarity-based fuzzy relational databases

Özgün Bahar, Adrian Yazici

Research output: Contribution to journalArticlepeer-review

20 Citations (Scopus)

Abstract

Fuzzy relational database models generalize the classical relational database model by allowing uncertain and imprecise information to be represented and manipulated. In this article, we introduce fuzzy extensions of the normal forms for the similarity-based fuzzy relational database model. Within this framework of fuzzy data representation, similarity, conformance of tuples, the concept of fuzzy functional dependencies, and partial fuzzy functional dependencies are utilized to define the fuzzy key notion, transitive closures, and the fuzzy normal forms. Algorithms for dependency preserving and lossless join decompositions of fuzzy relations are also given. We include examples to show how normalization, dependency preserving, and lossless join decomposition based on the fuzzy functional dependencies of fuzzy relation are done and applied to some real-life applications.

Original languageEnglish
Pages (from-to)885-917
Number of pages33
JournalInternational Journal of Intelligent Systems
Volume19
Issue number10
DOIs
Publication statusPublished - Oct 1 2004

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science
  • Human-Computer Interaction
  • Artificial Intelligence

Fingerprint Dive into the research topics of 'Normalization and lossless join decomposition of similarity-based fuzzy relational databases'. Together they form a unique fingerprint.

Cite this